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Domestication drastically changed crop genomes, fixing alleles of interest and creating different genetic populations. Genome-wide association studies (GWASs) are a powerful tool to detect these alleles of interest (and so QTLs). In this study, we explored the genetic structure as well as additive and non-additive genotype–phenotype associations in a collection of 243 almond accessions. Our genetic structure analysis strongly supported the subdivision of the accessions into five ancestral groups, all formed by accessions with a common origin. One of these groups was formed exclusively by Spanish accessions, while the rest were mainly formed by accessions from China, Italy, France, and the USA. These results agree with archaeological and historical evidence that separate modern almond dissemination into four phases: Asiatic, Mediterranean, Californian, and southern hemisphere. In total, we found 13 independent QTLs for nut weight, crack-out percentage, double kernels percentage, and blooming time. Of the 13 QTLs found, only one had an additive effect. Through candidate gene analysis, we proposed Prudul26A013473 as a candidate gene responsible for the main QTL found in crack-out percentage, Prudul26A012082 and Prudul26A017782 as candidate genes for the QTLs found in double kernels percentage, and Prudul26A000954 as a candidate gene for the QTL found in blooming time. Our study enhances our knowledge of almond dissemination history and will have a great impact on almond breeding.

Plants have evolved a range of adaptive mechanisms that adjust their development and physiology to variable external conditions, particularly in perennial species subjected to long-term interplay with the environment. Exploiting the allelic diversity within available germplasm and leveraging the knowledge of the mechanisms regulating genotype interaction with the environment are crucial to address climatic challenges and assist the breeding of novel cultivars with improved resilience. The development of multisite collections is of utmost importance for the conservation and utilization of genetic materials and will greatly facilitate the dissection of genotype-by-environment interaction. Such resources are still lacking for perennial trees, especially with the intrinsic difficulties of successful propagation, material exchange, and living collection maintenance. This work describes the concept, design, and realization of the first multisite peach (Prunus persica) reference collection (PeachRefPop) located across different European countries and sharing the same experimental design. Other than an invaluable tool for scientific studies in perennial species, PeachRefPop provides a milestone in an international collaborative project for the conservation and exploitation of European peach germplasm resources and, ultimately, as a true heritage for future generations.

Despite the availability of whole genome sequences of apple and peach, there has been a considerable gap between genomics and breeding. To bridge the gap, the European Union funded the FruitBreedomics project (March 2011 to August 2015) involving 28 research institutes and private companies. Three complementary approaches were pursued: (i) tool and software development, (ii) deciphering genetic control of main horticultural traits taking into account allelic diversity and (iii) developing plant materials, tools and methodologies for breeders. Decisive breakthroughs were made including the making available of ready-to-go DNA diagnostic tests for Marker Assisted Breeding, development of new, dense SNP arrays in apple and peach, new phenotypic methods for some complex traits, software for gene/QTL discovery on breeding germplasm via Pedigree Based Analysis (PBA). This resulted in the discovery of highly predictive molecular markers for traits of horticultural interest via PBA and via Genome Wide Association Studies (GWAS) on several European genebank collections. FruitBreedomics also developed pre-breeding plant materials in which multiple sources of resistance were pyramided and software that can support breeders in their selection activities. Through FruitBreedomics, significant progresses were made in the field of apple and peach breeding, genetics, genomics and bioinformatics of which advantage will be made by breeders, germplasm curators and scientists. A major part of the data collected during the project has been stored in the FruitBreedomics database and has been made available to the public. This review covers the scientific discoveries made in this major endeavour, and perspective in the apple and peach breeding and genomics in Europe and beyond.

[Background]: Peach (Prunus persica (L.) Batsch) is a major temperate fruit crop with an intense breeding activity. Breeding is facilitated by knowledge of the inheritance of the key traits that are often of a quantitative nature. QTLs have traditionally been studied using the phenotype of a single progeny (usually a full-sib progeny) and the correlation with a set of markers covering its genome. This approach has allowed the identification of various genes and QTLs but is limited by the small numbers of individuals used and by the narrow transect of the variability analyzed. In this article we propose the use of a multi-progeny mapping strategy that used pedigree information and Bayesian approaches that supports a more precise and complete survey of the available genetic variability., [Results]: Seven key agronomic characters (data from 1 to 3 years) were analyzed in 18 progenies from crosses between occidental commercial genotypes and various exotic lines including accessions of other Prunus species. A total of 1467 plants from these progenies were genotyped with a 9 k SNP array. Forty-seven QTLs were identified, 22 coinciding with major genes and QTLs that have been consistently found in the same populations when studied individually and 25 were new. A substantial part of the QTLs observed (47%) would not have been detected in crosses between only commercial materials, showing the high value of exotic lines as a source of novel alleles for the commercial gene pool. Our strategy also provided estimations on the narrow sense heritability of each character, and the estimation of the QTL genotypes of each parent for the different QTLs and their breeding value., [Conclusions]: The integrated strategy used provides a broader and more accurate picture of the variability available for peach breeding with the identification of many new QTLs, information on the sources of the alleles of interest and the breeding values of the potential donors of such valuable alleles. These results are first-hand information for breeders and a step forward towards the implementation of DNA-informed strategies to facilitate selection of new cultivars with improved productivity and quality.

[Background]: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach., [Results]: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3–5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average)., [Conclusions]: This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the typical long cycles involved in peach productions. All together, these results are very promising for the application of genomic selection to peach breeding programmes.

Background: Highly polygenic traits such as fruit weight, sugar content and acidity strongly influence the agroeconomic value of peach varieties. Genomic Selection (GS) can accelerate peach yield and quality gain if predictions show higher levels of accuracy compared to phenotypic selection. The available IPSC 9K SNP array V1 allows standardized and highly reliable genotyping, preparing the ground for GS in peach. Results: A repeatability model (multiple records per individual plant) for genome-enabled predictions in eleven European peach populations is presented. The analysis included 1147 individuals derived from both commercial and non-commercial peach or peach-related accessions. Considered traits were average fruit weight (FW), sugar content (SC) and titratable acidity (TA). Plants were genotyped with the 9K IPSC array, grown in three countries (France, Italy, Spain) and phenotyped for 3-5 years. An analysis of imputation accuracy of missing genotypic data was conducted using the software Beagle, showing that two of the eleven populations were highly sensitive to increasing levels of missing data. The regression model produced, for each trait and each population, estimates of heritability (FW:0.35, SC:0.48, TA:0.53, on average) and repeatability (FW:0.56, SC:0.63, TA:0.62, on average). Predictive ability was estimated in a five-fold cross validation scheme within population as the correlation of true and predicted phenotypes. Results differed by populations and traits, but predictive abilities were in general high (FW:0.60, SC:0.72, TA:0.65, on average). Conclusions: This study assessed the feasibility of Genomic Selection in peach for highly polygenic traits linked to yield and fruit quality. The accuracy of imputing missing genotypes was as high as 96%, and the genomic predictive ability was on average 0.65, but could be as high as 0.84 for fruit weight or 0.83 for titratable acidity. The estimated repeatability may prove very useful in the management of the

Peach was domesticated in China more than four millennia ago and from there it spread world-wide. Since the middle of the last century, peach breeding programs have been very dynamic generating hundreds of new commercial varieties, however, in most cases such varieties derive from a limited collection of parental lines (founders). This is one reason for the observed low levels of variability of the commercial gene pool, implying that knowledge of the extent and distribution of genetic variability in peach is critical to allow the choice of adequate parents to confer enhanced productivity, adaptation and quality to improved varieties. With this aim we genotyped 1,580 peach accessions (including a few closely related Prunus species) maintained and phenotyped in five germplasm collections (four European and one Chinese) with the International Peach SNP Consortium 9K SNP peach array. The study of population structure revealed the subdivision of the panel in three main populations, one mainly made up of Occidental varieties from breeding programs (POP1OCB), one of Occidental landraces (POP2OCT) and the third of Oriental accessions (POP3OR). Analysis of linkage disequilibrium (LD) identified differential patterns of genome-wide LD blocks in each of the populations. Phenotypic data for seven monogenic traits were integrated in a genome-wide association study (GWAS). The significantly associated SNPs were always in the regions predicted by linkage analysis, forming haplotypes of markers. These diagnostic haplotypes could be used for marker-assisted selection (MAS) in modern breeding programs.

“FruitBreedomics” European project has been designed by an international consortium including scientists, stakeholders and breeding companies. One of its aims is to increase the efficiency of breeding programs in apple (Malus ×domestica) and peach (Prunus persica) by enabling Marker Assisted Breeding (MAB) using novel genomic tools. In the frame of this project, five peach mapping populations from the UGAFL (Unité de Génétique et Amélioration des Fruits et Légumes) peach breeding program (two intraspecific F2, two interspecific F1 derived from P. davidiana and one self-pollinated derived from ‘Bolinha’) segregating for mendelian traits and/or Quantitative Trait Loci (QTLs) for pest resistance and fruit quality were genotyped using the 9K SNP Illumina Infinium II Bead-chip delivered by the International Peach SNP Consortium (IPSC). Based on these data, genetic maps were then constructed; however mapping results were contrasted depending on the population considered. All maps aligned with the 8 pseudo-molecules of the Prunus persica Whole Genome sequence v1.0 (IPGI), but the best polymorphisms and coverage were obtained with the F2 populations, for which twenty to twenty-nine percent of the SNPs were polymorphic covering 500 loci on average. However, these loci were unevenly distributed, although covering most of the peach genome. In contrast, for the F1 populations, only 5% of the SNPs were polymorphic in P. davidiana and the selfing of ‘Bolinha’ resulting in low coverage and very heterogeneous distributions. As primary consequence, this demonstrates the poor transferability of such a tool between species, even tightly related, and additionally highlights the relatively low efficiency of SNPs in term of useful polymorphism when parents belong to close peach germplasms. Consequently, regions containing QTLs and major genes could be insufficiently covered and need additional SNP development for MAB. The relevancy of using general medium-range SNP bead-chips for breedin

The present study investigates the genetic determinism of flowering and maturity dates, two traits highly affected by global climate change. Flowering and maturity dates were evaluated on five progenies from three Prunus species, peach, apricot and sweet cherry, during 3–8 years. Quantitative trait locus (QTL) detection was performed separately for each year and also by integrating data from all years together. High heritability estimates were obtained for flowering and maturity dates. Several QTLs for flowering and maturity dates were highly stable, detected each year of evaluation, suggesting that they were not affected by climatic variations. For flowering date, major QTLs were detected on linkage groups (LG) 4 for apricot and sweet cherry and on LG6 for peach. QTLs were identified on LG2, LG3, LG4 and LG7 for the three species. For maturity date, a major QTL was detected on LG4 in the three species. Using the peach genome sequence data, candidate genes underlying the major QTLs on LG4 and LG6 were investigated and key genes were identified. Our results provide a basis for the identification of genes involved in flowering and maturity dates that could be used to develop cultivar ideotypes adapted to future climatic conditions.

One of the objectives of the ISAFRUIT Project was to perform genetic analyses in four populations of Prunus, two of peach (P. persica) and two of apricot (P. armeniaca), in order to identify major genes and quantitative trait loci (QTLs) for characters related to fruit quality. This required the construction of saturated marker maps in each of these populations. Marker maps were available for an intra-specific peach × peach F2, a BC2 peach × P. davidiana (using peach as the recurrent parent), and an apricot × apricot F1. We have further saturated these maps mainly with SSR (simple sequence repeat) markers. A new map, constructed uniquely from SSRs was prepared for a fourth apricot × apricot F1 population. Using anchor markers, we compared these four maps with the reference Prunus map, constructed using an almond × peach F2 population. As previously observed, conservation of synteny and co-linearity were the general rule, providing additional evidence of the high level of similarity between all Prunus genomes. Comparisons of genetic distances between the maps suggested that those involving similar genomes had higher levels of recombination than those with more distant genomes, particularly the inter-specific crosses.